RECOMMEND FOR SHOPIFY


ALREADY USED BY 500+ BRANDS.
HYPER-PERSONALIZED RECOMMENDATIONS.
OLD WAY
Using customer histories to generate recommendations to future web visitors.
Only creates relevant personalization for up to 10% of your visitors.
This is how regular personalization works.
NEW WAY
Using live visitor buying signals to generate hyper-relevant recommendations on the fly.
Unlocks relevant personalization for remaining 90% of your visitors.
Amazon calls this Hyper-Personalization.
“We have been in search of a good personalization and recommendation tool for our Shopify Plus store for a couple years now. A 58% increase in our average order amount is just one result from this app. Very easy to use and their team is always helpful in answering any questions you have. If your company is looking to get into personalization, then you really need to try out Obviyo.”
– Jeff Moriarty, Director of Marketing, MySupplementsStore.com
RESULTS SPEAK FOR THEMSELVES.
+243%
Revenue per visit
Pat McGrath
+275%
Revenue per visit
Lilly Lashes
+391%
Revenue per visit
Synergee
+408%
Revenue per visit
Supplement Warehouse
* Measure of the quality of recommendations: revenue-per-visit (RPV) difference between cohort of visitors who engaged with recommendations vs. cohort of visitors who did not.
CASE STUDY
Can Hyper-Personalized Recommendations Fix Shopify’s Mobile Product Discovery Problem? (Spoiler: Yes)

MOBILE RESULTS
Without Hyper-Personalization:
Time on site: 153 seconds
Revenue per visit: $3.59
With Hyper-Personalization:
Time on site: 554s (▲ 236%)
Revenue per visit: $17.86 (▲ 600%)
Time to results: 4 weeks
UNIQUE INSIGHT
Mobile shoppers spend less time on site compared to desktop visitors.
Visitors’ average time on site directly correlates with revenue per visitor (RPV) metric, which explains why mobile revenue per visit is way below desktop RPV.
MERCHANT VALUE
With hyper-personalized product recommendations, this brand is boosting mobile visitor time on site. As a result, they’re significantly increasing revenue-per-visit (RPV) of visitors who are engaging with recommended products.
“If you are looking to replicate the Amazon product discovery experience on your own site to influence more conversions and sales, this is the app for you. We went live quickly, and continue to add automated recommendations across our whole site, including the cart. The support team have been very helpful during our initial rollout, and the Amazon Personalize machine learning is a seriously powerful stuff!”
– Head of eCommerce, Synergee Fitness
WHAT'S IN IT FOR YOU?
Win New Customers
On average, 90% of your visitors never add a product to the cart and leave.
Hyper-personalization will unlock the revenue potential from your ‘cold’ traffic, from visitors who are your current non-customers.
Unlock Mobile Revenue
Mobile shoppers have different needs and they act differently. Buying sessions are much shorter than on desktop.
Hyper-personalized recommendations will increase time on site and boost mobile revenue.
Increase Lifetime Value
Getting more revenue from existing customers is challenging.
Hyper-personalization enables seamless customer engagement along the entire lifecycle to upsell and cross-sell the existing customers.
MEET RECOMMEND.
Recommend is a Shopify Plus certified app, making hyper-personalization possible for merchants of any size.
All powered by Amazon Personalize – the machine learning technology driving product recommendations on Amazon.com.
“Obviyo allows brands of any size on the Shopify marketplace to benefit from hyper-personalization based on the same technology that is powering product recommendations on Amazon.com.”
– Zoe Hillenmeyer, Head of Business Development for AI, Amazon – AWS
OLD WAY
Use of historic data to train algorithms to recognize buying patterns of existing customers.
OLD RESULT: Recommendations that are only relevant for up to 10% of visitors who have the same preferences as existing customers or those that are very similar to them.
NEW WAY
Use of live customer actions and context to make hyper-personalized product recommendations in real time.
NEW RESULT: Unlocking a revenue potential of remaining 90% of visitors who every day have a good reason to visit a site and leaving without every finding a product of interest.
THE BREAKTHROUGH DISCOVERY
From 20 years of continuous experimentation and innovation at Amazon.com, the machine learning team learned visitor actions and context are much better predictors of customer needs and preferences than historic data alone.
This has disrupted the personalization game and forged a new generation of machine learning algorithms. Capable of making real-time recommendations based on live visitor activity.
EASY TO USE.

Personalization Playbooks
Dozens of pre-built product recommendation templates aimed at different personas sending different buying signals – gets you started in minutes.
Email Integration
Expand hyper-personalization across multiple channels. Seamless experiences between web and email marketing.
Visual Editor
Intuitive ‘no-code’ editor for both mobile and desktop UX. Always stay on brand.
Deep Insights
Learn what recommendation strategies perform best. Iterate until you uncover your top performing portfolio of hyper-personalized recommendations.
Real-Time Performance
To achieve top hyper-personalization results you need an app that is architected for the greatest real-time performance.
Recommend sits on top of Obviyo’s HyperX Cloud. This maximizes CDN capability to provide high speed visitor tracking, multi-environment data exchanges, and machine learning that provides recommendations related to live visitor actions in milliseconds.
Amazon’s Algorithms
Hyper-personalization is a new science. Development requires time, deep expertise, and a big budget.
Recommend is powered by the same algorithms that are driving product recommendations (and billions in monthly sales) on Amazon.com.
Shopify Integration
Adoption of enterprise grade solutions like Recommend is only possible with ease of use.
Recommend is tightly integrated into your store. All you have to do is activate the app in your Shopify admin panel.
HYPER-PERSONALIZATION BY THE NUMBERS*.
35%
of all sales influenced by personalization.
+11%
sales gains attributed to personalization.
+54%
more likely to become repeat buyers.
*Based on independent analyst estimates of Amazon.com.
CASE STUDY
What Running Dozens of Hyper-Personalized Recommendations on This Shopify Plus Store Taught Us About Growing New Revenue

SITE RESULTS
Starting point:
% of engaged visitors: 1.2%
% of revenue influenced: 2.4%
End point:
% of engaged visitors: 9.6% (▲ 700%)
% of revenue influenced: 37.9% (▲ 1,479%)
Timeframe: 4 months
UNIQUE INSIGHT
Most Shopify stores have a few product recommendations on a handful of pages, like product or cart pages, while majority of their site is a static content.
Amazon.com is blowing ‘conventional wisdom’ out the water and treating almost the entire site as a dynamic, product recommendation driven content.
This case study proves the value of Amazon’s approach. As merchant was increasing the number of recommendations the percentage of visitors engaging with product recommendations increased in a linear way, while new revenue influenced by recommendations increased exponentially.
MERCHANT VALUE
By placing a wide variety of product recommendations aimed at different buying personas taking different actions on the site under different context merchants will unlock a revenue potential of 90% of non-buyer visitors who never engage with the brand today.
Automated Setup
By activating Recommend you will initialize fully automated workflows to download your data, train machine learning algorithms, and place a small tag into your site theme so we can learn from visitors and deliver live recommendations.
Concierge Service
Our success management team will create and style product recommendations on your behalf while incorporating your feedback until you satisfied and ready to go live.
Measurable Results
See for yourself if new recommendation algorithms that use visitors’ real-time actions and context to unlock revenue from 90% of your ‘cold’ traffic are performing well on your site.
FAQ
Is my data safe and secure?
Yes.
Obviyo Recommend is a Shopify Plus certified app. Which means we comply with Shopify’s own high data privacy and security requirements.
To learn more about our data privacy and security please check our Privacy Policy.
Note: We never share data with Amazon.
Will you slow our page load time?
Relative to your existing page load time, the impact is minimal.
During the Shopify Plus certification process we had to run page load time stress tests to demonstrate tag loading speed complies with Shopify’s high standards.
Note: When evaluating our tag load times Merchants should have in mind that our tag is an asynchronous tag. Our tag loads in parallel with other page content. So, if our tag loads in 200ms that does not mean the net impact on the page load time is 200ms. Instead, it is a fraction of that – since during the 200ms time interval a browser also loaded 4-5 other content items in parallel.
Is it easy to add your app to my Shopify store?
Yes. Just install the app and our system will start multiple automated workflows. This will connect our app to your Shopify store data, automatically place our tag to your theme, configure your recommendation algorithms, map data, and many other things.
Can we style the recommendations to match our theme?
Yes. Our team will follow your directions to customize the recommendation titles and brand style.
How do you know where to put recommendations on my site?
We’ll do it on your behalf in our admin panel. We identify unique ‘markers’ in your store’s source code and place recommendations before or after those markers.
These markers will appear as a named locations in the admin drop down box for your future ongoing use of our application.
What happens if we decide not to use your app after 7-day challenge?
Nothing.
We will pause your live recommendations, enabling you to change your mind and hypothetically use our app again in the future.
There is no need to uninstall app. Since you are not using, you will not be charged.